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Habitat International 38 (2013) 100e105Contents lists availableHabitat International

journal homepage: www.elsevier .com/locate/habitat intGreenhouse gas emission reduction options for cities: Finding the Coincidenceof Agendas between local priorities and climate change mitigation objectives

Hari Bansha Dulal*, Sameer AkbarThe World Bank, 1818 H Street, NW, Washington, DC 20433, USAKeywords:Greenhouse gasCitiesClimate change mitigationCo-benefitsSynergiesDeveloping countries* Corresponding author. Tel.: 1 571 288 1854.E-mail address: hbdulal@gmail.com (H.B. Dulal).

0197-3975/$ e see front matter 2012 Elsevier Ltd.doi:10.1016/j.habitatint.2012.05.001a b s t r a c t

Cities are the major contributors to global greenhouse gas (GHG) emissions. They account for about 75%of global energy consumption and up to 80% of global greenhouse gas emissions. With the ongoing rapidincrease in urban population, expansion of middle class in urban centers in developing countries, andavailability of cheaper vehicles such as Tata Nano and Bajaj RE60 in India, the demand for energy andassociated emissions from cities are expected to grow rapidly. Though cities are in a better position tomitigate climate change, it does not necessary mean that there is a willingness on their part to capitalizeon these mitigation opportunities. Climate change mitigation is not the priority for them because theyface a number of competing priorities including local economic growth and development and servicedelivery. This paper suggests a range of policy tools that can help cities achieve both local priorities aswell as reduce emissions, including GHGs. The suggested policies will be effective when usedsynergistically.

2012 Elsevier Ltd. All rights reserved.Introduction

Even though urban areas constitute less than 3% of the worldslivable land area, approximately 50%of theworlds population todaylives in urban areas. By 2030, 60% of the worlds population will beliving in cities. The share of urbanpopulationwill have grown to 75%by2050 (Mills, 2007;UN, 2007). The urbanized area has increased inalmost every developing country. The urbanized area of the city ofYazd, Iran, increased from 1843 ha in 1975 to 13,802 ha in 2009(Shahraki et al., 2011). Between 1989 and 2009, the builteup area inthe Greater Asmara Area (GAA), the capital of Eritrea, has tripled(Tewolde & Cabral, 2011). The surface area of Mexican city of Gua-dalajara grew1.5 times faster than thepopulation between1970and2000. Similar is the case in Antananarivo, the capital ofMadagascar;Cairo, the capital of Egypt; and Mexico City, the capital of Mexico;Johannesburg, South Africa (UNHABITAT, 2010). As urbanizationtends to increase with socio-economic development, the levels ofurbanization are generally projected to rise in developing countriesin the future. By 2030, the less developed regions are expected tohave 56% of their population living in urban areas, which is aboutthree times the proportion they had in 1950 (18%) (UN, 2006).

The ongoing rapid urbanization has already led to tremendousincrease in energy consumption and associated emissions. In India,All rights reserved.for example, the use of diesel in the transport sector has increasedfrom 73% of the total in 1991 to 81% in 2000 (Zhou &McNeil, 2009).If the current trend is to continue, motorized traffic volume in Indiawould reach 130,000 billion passenger kilometers. Compared to theyear 2000, this would result in a five-fold increase in energydemand and carbon emissions in transport by 2020 (Singh, 2006).The trend is quite similar in many developing countries andemerging economies. InMalaysia, from 6.8 million vehicles in 1995,the motor vehicle ownership increased to 18 million, in 2008. Withan annual growth rate of 7.78%, it almost tripled in a little morethan a decade. The transport sector alone accounts for 35.5% of thetotal energy consumption in Malaysia (Ong, Mahlia, & Masjuki,2011). Under business as usual (BAU) scenario, direct energydemand and GHG emissions from the road transport is expected toreach 734 million tons of oil equivalent and 2384 million tonscarbon dioxide equivalent by 2050 in China. The projected increaseis 5.6 times more than the 2007 level (Ou, Zhang, & Chang, 2010).

In reality, the increase in emissions could be much higher thanthe one projected by BAU scenario. BAU scenarios often do not takeinto consideration social and cultural changes that are actuallyhappening in many developing countries. In India, for instance,because of the social status attached to vehicle ownership, house-holds have started owning more than one private vehicle. In future,they may be in a position to afford a vehicle for each and everymember of the household. If that were to happen, GHG emissionswould be much higher than projected under BAU scenario. It is notonly the transport sector, where the demand for energy is growing.

Delta:1_given nameDelta:1_given nameDelta:1_surnameDelta:1_given namemailto:hbdulal@gmail.comwww.sciencedirect.com/science/journal/01973975http://www.elsevier.com/locate/habitatinthttp://dx.doi.org/10.1016/j.habitatint.2012.05.001http://dx.doi.org/10.1016/j.habitatint.2012.05.001http://dx.doi.org/10.1016/j.habitatint.2012.05.001

Table 1Ranking of selected megacities based on total suspended particulate emission androad travel speed.

Megacities in 2000 Total suspendedparticulates (mg m3)

Average road speedmiles per hour

Rank Rank

Tokyo 40 [15] 16.2 [9]Mexico City 201 [10] 14.0 [6]New York e Newark 27 [18] 23.9 [14]So Paulo 53 [14] 15.0 [8]Mumbai (Bombay) 243 [9] 13.8 [5]Kolkata (Calcutta) 312 [6] naShanghai 246 [8] 12.4 [4]Buenos Aires 185 [11] 18.6 [10]Delhi 405 [4] 14.4 [7]Los Angeles - Long

Beach - Santa Ana39 [16] 29.5 [15]

Osaka e Kobe 34 [17] 20.5 [13]Jakarta 271 [7] 11.6 [2]Beijing 377 [5] 11.1 [1]Rio de Janeiro 139 [13] 18.6 [10]Cairo 593 [2] 12.4 [3]Dhaka 516 [3] naMoscow 150 [12] 18.6 [10]Karachi 668 [1] na

Source: Adapted from Parry and Timilsina (2010).

Fig. 1. Costs for reducing health impacts from air pollution by 50% (bn V in 2030).Source: Amann et al. (2010).

H.B. Dulal, S. Akbar / Habitat International 38 (2013) 100e105 101There has been a tremendous growth in energy consumption andemissions in the industrial sector as well. Approximately 188.32million tons of CO2 was emitted from the city of Shanghai alone in2008 (Liu, Geng, & Xue, 2011). The situation is quite similar in otherbig Chinese cities. Carbon emission in the city of Nanjing hasincreased by about 50% in the last decade. Industrial energyconsumption, industrial processes, and transportation accountedfor 37e44%, 35e40% and 6e10% of urban emissions respectively (Bi,Zhang, Wang, & Liu, 2011). Most cities are quite aware of the factthat the existing carbon intensive path is unsustainable. But giventhe increase in public desire to own vehicles and technologies thatrequire energy, increase in urban industrialization and increase inconsumption of carbon intensive processed foods, emissions aregrowing not only in mega cities in developing countries, but also insecond-tier cities. Cities in developing countries are quite aware ofthe fact that urgent measures are needed to move away from highemissions pathway, but given the host of local priorities, lack ofcapacity, resources, and understanding of policy tools that can helpthem achieve both local priorities as well as emissions reduction,they are finding it increasingly difficult to contain rising emissions.

Can cities continue to afford undermining growingemissions?

Emissions from cities mainly depend on four factors. First, theeconomic base of a city, i.e. whether the city is industrial or serviceoriented. Second, its urban form, i.e. density and location patternsof its settlement. Third, the lay out and structure of its trans-portation system. Fourth, waste management system, i.e. efficiencyand effectiveness of waste collection and disposal. In almost everycity in developing country, all of the aforementioned factors are atplay. Economic base is getting more industrial, urban form isbecoming less dense, the lay out and structure of transportationsystems increasingly favor private transportation, and withincrease in waste volume, waste management is becomingincreasingly chaotic and inefficient. Given the nature of the prob-lems they face, cities are more interested in adopting policies andprograms that provide greater local benefits. Climate mitigationbenefits, hence, will have to come from the policies and programsthat are aimed at solving local problems. For example, increasingtraffic congestion in many developing countries cities is hurtingurban economy. The costs of congestion are 2.6 and 3.4 and inMexico City and Buenos Aires (UNEP, 2011). In 1996, the costs oftraffic congestion in Bangkok, Kualalumpur, Jakarta, and Manilawere 2.1, 1.8, 0.9, and 0.7% of GDP (ESCAP, 2007). In 1994, Santiago,Chile incurred US$286 million (0.59% of national GDP) in conges-tion cost (Creutzig & He, 2009). Congested cities are also the toppolluted cities. There appears to be a correlation between conges-tion and pollution as the top polluted cities polluted cities are alsothe ones, where road speed average is low (see Table 1).

Air pollution entails a massive cost amounting tomillions a year.In 2001, the local air pollution costs for the Philippines (MetroManila, Davao, Cebu, and Baguio) were 432 million or 0.6% of GDP(World Bank, 2002). It was US$181.4 million or 1% of the GDP forJakarta, Indonesia for the year 1998 (ADB, 2002). Local air pollutioncost incurred by China is higher than other countries, for whichdata is available. In 2000, the city of Beijing alone incurred US$974million or 3.3% of GDP in local air pollution costs (based onwillingness-to-pay methodology) (Deng, 2006). Given that many ofthe traditional air pollutants and greenhouse gases have commonsources, their emissions interact in the atmosphere, and separatelyor jointly they cause a variety of environmental impacts on thelocal, regional, and global scales, emission control strategies thatsimultaneously address air pollutants and greenhouse gases maylead to a more efficient use of the resources on all scales (ESA,2004). In developing and emerging economies, where economicand social developments e not climate change mitigation e are thetop priorities, integration/policy coherence is especially relevant. Inaddition to providing greater cumulative climate benefits (seeFig. 1), policy integration and programmatic coherence is alsodesirable because of the cost-effectiveness.

Fig. 1 illustrates that China can dramatically save costs byadopting a smart mix of measures to reduce air pollution andgreenhouse gas emissions even if the goal is to achieve ambient airquality. Compared to the most cost-effective way for halvingnegative health impacts from air pollution using only air pollutioncontrol measures, using measures to lower air pollution andgreenhouse gas emissions simultaneously is much more cost-effective. The cost saving could results in a 9% reduction in GHGemissions (Amann et al., 2010). Well-designed air pollution controlstrategies can help achieve ambient air quality and at the same timereduce emissions of greenhouse gases.

Greenhouse gas emissions reduction would benefit both thecurrent and the future city inhabitants as GHG emissions reductionis not only an important issue of the current time but also anintergenerational distribution issue. The current inhabitants wouldbenefit greatly by decreased health care costs and reduction inproductivity loss, while the future inhabitants would benefit fromreduced global warming from GHG emissions and its conse-quences, which is increasingly being witnessed with each passing

H.B. Dulal, S. Akbar / Habitat International 38 (2013) 100e105102year. It might be in the best interest of cities to reduce emissionsnow because the costs of repairing damage and improving envi-ronmental quality once the economy is past its turning point will besignificantly higher than the cost of preventing the damage throughearly mitigation.

Maintaining environmental quality is also crucial if cities wantto transition to knowledge-based economy and brighten theireconomic attractiveness. Urban environmental quality is importantto attracting and retaining the talent that drives wealth creationin knowledge-based economies. Skilled workers look for commu-nities with specific attributes such as user-friendly transit;commuter bike lanes; a clean, healthy environment; anda commitment to preserving natural resources for enjoyment andrecreation (Florida, 2000). By 2030, cities that will brighten theireconomic attractiveness will do so while also curbing local pollu-tion (e.g. Ankara, Auckland, Barcelona, Krakow, Lille, Melbourne,Montreal, Monterrey and Toronto). On contrary, cities such asChicago, Los Angeles, New York, Osaka, Paris, Philadelphia, Seouland Tokyo risk losing economic attractiveness if their currentpollution trends continue unabated (OECD, 2010).

Leveraging local priorities for urban green house gasreduction

Rapid urban growth in developing countries is seriously out-stripping the capacity ofmost cities to provide adequate services fortheir citizens. For cities in developing countries struggling to meettheir local priorities, stand-alone climate change mitigationprogram is an unnecessary diversion and waste of scarce resources.Stand-alone urban climate change mitigation policies have beenfound unacceptable even in developed countries. Using an inte-grated city model for the city of Paris, Vigui and Hallegatte (2012)demonstrate that stand-alone mitigation policies are unlikely to bepolitically acceptable and emphasize the need to mainstreamFig. 2. Framework for GHG emclimate policy within urban planning. Given the traffic congestioncosts, it is quite natural to expect cities like Mexico City, BuenosAires, Bangkok, Kuala Lumpur, and Jakarta to be more interested inputting their resources toward enhancing mobility rather thanreducing GHG emissions. They would only be interested in GHGemissions reduction issue if the policy tools or measures suggestedcontribute significantly toward meeting local priorities, which intheir case is, easing traffic congestion. GHG emissions reductionwillhave to come through policies and programs aimed atmeeting localpriorities such as traffic congestion easing, air pollution control, andwaste management, etc. There are several policy tools that can helpdeveloping countries cities meet their local priorities and at thesame time contribute toward urban GHG reduction (see Fig. 2).

Urban development interventions

Urban spatial expansion results mainly from three powerfulforces: a growing population, rising incomes, and fallingcommuting costs (Brueckner, 2000). In most cities in developingcountries, the first two factors are already in play. The level of urbanexpansion is further expected to grow because over the next30 years virtually all of the worlds population growth is expectedto occur in urban areas in developing countries (Cohen, 2006).Withurban expansion, the economic cost of congestion and pollution,which is already high given the size of economies, will furtherincrease and have a greater adverse impact on local economy. Usingthe concentrationeresponse coefficients for cough, breathlessness,wheezing and cold, and illnesses such as allergic rhinitisand chronic obstructive pulmonary disease (COPD), Patankarand Trivedi (2011) estimate that the total monetary burden,including personal burden, government expenditure and societalcost for the city of Mumbai in India, is US$113.08 million for a 50-mg/m3 increase in PM10 and US$ 218.10 million for a 50-mg/m3

increase in NO2.issions reduction in cities.

H.B. Dulal, S. Akbar / Habitat International 38 (2013) 100e105 103By adopting some of the suggested policy tools such as highemployment and residential density development, cities can effec-tively contain the ongoing rapid urban expansion and at the sametime achieve air quality improvement benefit. Policy tools used toachieve higher density development have been found to reduce airpollution, traffic congestion, and energy use. Evidence suggests thatadoption policy tools that promote high density reduce vehicle-based emissions by shortening commuter journeys and encour-aging non-auto travel (Cervero&Kockelman,1997; Dulal, Brodnig, &Onoriose-Green, 2011; Lin & Yang, 2009;Messenger & Ewing,1996).Using data from 84 cities in the United States, Europe, Australia andAsia, Lyons, Kenworthy,Moy, and dos Santos (2003) show that thereis direct air pollution reduction benefits from minimizing theoutward growth of cities. Emissions reduction comes throughreduction in private vehicle use. Transit use rises sharply whenresidential density increases from 7 to 16 dwelling units/acre(Smith, 1984). European countries, with higher densities and morecentralized land-use patterns have lower levels of private vehiclesuse when compared to the U.S., where urban density is low andpopulation is dispersed (Giuliano & Narayan, 2003).

Evidence shows that it is possible to grow without experiencingcongestion, pollution, and reducing public space. For over fourdecades, the city of Curitiba in Brazil has been utilizing urbanpolicies as a means to guide and induce urban growth in order toimprove quality of life, promote social equity, and preserve thenatural environment. Compared to other Brazilian cities like SaoPaulo and Rio de Janeiro, the cost of congestion in Curitiba issignificantly low. In 2002, fuel use due to severe traffic congestion,which was estimated at a value of US$1, was approximately 13 and4 times less in per capita terms than those in Sao Paulo and Rio deJaneiro respectively. Likewise, the congestion cost and per capitaproductivity loss due to time spent in severe congestion in Curitibawas approximately 11 and 7 times lower than in Sao Paulo and Riode Janeiro respectively. Despite of three-fold increase in the pop-ulation density between 1970 and 2008, the average green area perperson in Curitiba actually increased from 1 km2 to over 50 km(UNEP, 2010).

Urban transport interventions

Rising urban income, declining vehicle price, and increasingvehicle stock have all led to rapid growth in vehicle ownership anduse in cities in developing countries. As the middle class in cities indeveloping countries get more affluent and afford to buy privatevehicles, they do so. This increases traffic congestion and causesfurther deterioration of the environmental quality. Private vehicleseventually end up dominatingmuch of the available urban space bydisplacing more efficient public transport, motorbikes, and bicycles(Banister, 2011). Between 1980 and 1995, the total number ofregisteredmotor vehicles increased bymore than 11 times from2 to25 million in China (Gan, 2003). In India, the number of cars hasincreased sevenfold between 1981 and 2002, (Pucher,Korattyswaropam, Mittal, & Ittyerah, 2005). Increase in privatevehicle ownership and lack or deterioration of public transportationis causing traffic gridlock and environmental quality deteriorationin cities in developing countries. Increase in vehicle ownership andits use will further increase socio- economic and environmentalexternalities (negative) in coming years and decades.

Cities can reduce urban transport externalities by implementingfiscal (fuel tax, vehicle tax, parking charges, and congestion charges)and regulatory policy instruments (fuel economy standards, emis-sion standards, inspection maintenance programs, vehicle utiliza-tion e.g., full or partial bans) (Timilsina & Dulal, 2008, 2009, 2010).Congestion charge, for example, can enhance mobility by discour-aging private vehicle ownership and use. In London, the congestioncharge system led to the reduction in city-center traffic by 12%, ofwhich, 50e60% shifted to public transport (Transport for London,2004). The ex-post evaluation of the quantified impacts of thecongestion charging scheme in London shows that distance trav-eled across Londonwere reduced by approximately 211 million peryear with a 5 charge and 237 million with an 8 charge (Evans,2007). The suggested policy tools also provide GHG reductionbenefits. The value of CO2 emissions saved by congestion chargeintroduced in London is estimated to be about 2.3 million, with 5and 2.5million, with 8 (Evans, 2007). Evidence demonstrates thatfuel taxes reduce travel demand, fuel consumption, and emissions(Hirota, Poot, & Minato, 2003; Sterner, 2006). Using the data from68 large cities worldwide, Hirota et al. (2003) show that every 1%increase in the fuel tax could reduce vehiclemiles traveled (VMT) by0.042%. Like congestion charge and fuel tax, vehicle tax is anotherfiscal policy instruments that has both congestion and emissionsreduction potential. Singapore has successfully used vehicle tax asthe primary measure for discouraging private transportation andthereby reducing congestion and air pollution. Policies such as highvehicle ownership taxes, including the Additional Registration Fee(ARF), the Excise Duty and the annual Road Tax, and the VehicleQuota System (VQS) have successfully contained congestion andother traffic externality problems in Singapore (Willoughby, 2000).

Infrastructure interventions

Increase in temperature and extreme heat events are going toincrease energy demand in the coming years and decades.Increased energy use is being observed not only in the cities in thedrier parts of the world, but also in otherwise, comparatively coolercities in the North America and Europe. For example, in Toronto anaverage temperature increase of 3 C was found to be associatedwith a 7% increase in mean peak electric demand (Colombo, Etkin,& Karney, 1999). By 2030, the average number of days in Julyrequiring air conditioning in Boston, USA could increase by over24% with a corresponding rise in energy use. In Boston, climatechange will be responsible for 25e40% of increase in energydemand (Kirshen et al., 2004). By 2050, the typical air conditionedoffice building in London is estimated to increase its energy use forcooling by 10%, and by 2080, the increase is expected to be around20% (LCCP, 2002). The rise in temperature in cities in Africa, Asia,and Latin America that get really hot during the summer couldsignificantly increase urban energy demand. One of the ways todeal with the increase in energy demand is retrofit existing agedbuilding stock. For example, in many cities in India, a largeproportion building stock is aged, dilapidated, and do not meetcontemporary standards of building safety. Retrofitting of existingaged building stock could help reduce both future energy costs andGHG emissions (Satterthwaite, Huq, Pelling, Reid, & RomeroLanako, 2007). Cities can also contain energy demand and cost byintroducing energy efficiency programs.

Table 2 illustrates some of the cost-effective infrastructureinterventions that can help reduce energy costs and produce GHGemissions reduction co-benefits. With the modest payback timeand implementation cost, some of these programs hold a tremen-dous replication potential in cities in developing countries.

Waste sector interventions

With increase in urban income and change in lifestyle, urbanresource consumption pattern is changing in developing countries.The change in resource consumption pattern is having a significantdirect impact on the waste volume and associated emissions. InChina, from 31.3 million tons in 1980, the total MSW volumeincreased to 212million tons in 2006. Thewaste generation rate has

Table 2Selected energy efficiency measures.

Measure Status Estimated annual CO2reduction (tons)

Estimated annualcost Savings

Estimated implementationcost

Payback

LED traffic signals Existing Negligible $1500 $1785 1.2 yearsConvert remaining signals to LED Proposed Negligible $3773 $4480 1.2 years10% energy efficiency program - residential Proposed 3793 tons $819,392 $5000 0 years10% energy efficiency program e commercial Proposed 780 tons $44,423 $2000 0 yearsEfficiency upgrades to town buildings Proposed 136 tons $64,901 $0 0 yearsEfficiency upgrades to school buildings Proposed 55 tons $14,489 $0 0 yearsWood-chip heating system at Brattleboro union high school Planned 378 tons $55,000 $300,000 5.5 yearsConversion of town fleet vehicles to biodiesel Proposed 72 tons $0 $5545 0 yearsUse of compact fluorescents in residences Proposed Negligible $146,678 $77,632 0 yearsTotal Proposed 5214 tons $1,150,156 $396,442

Source: Adapted from Town of Brattleboro (2003).

H.B. Dulal, S. Akbar / Habitat International 38 (2013) 100e105104increased from 0.50 kg/capita/day in 1980 to 0.98 kg/capita/year in2006 (Zhang, Tan, & Gersberg, 2010). The waste generated in urbanareas is expected to further increase in coming decades in cities indeveloping countries. From 0.49 kg/person/day in 1995, wastegenerated in urban areas is expected to increase to 0.6 kg by 2025 inBangladesh (Ray, 2008). With increase in waste volume, waste-based emissions are also increasing. In So Paulo and Barcelona,waste and wastewater account for 23.6 and 24% respectively of thetotal GHG emissions. Similarly, waste and wastewater togetheraccount for 36.5% of GHG emissions in Rio de Janeiro (Dodman,2009). The troubling aspect of the waste-based emission is that itis expected to grow, and grow rapidly. In Southeast and South Asia,methane (CH4) emission from wastewater is expected to increaseby almost 50% between 1990 and 2020 (US EPA, 2006).

Cities in developing countries can effectively deal with the risingwaste volume and waste-based emissions by initiating waste-to-energy, composting, and recycling programs. Exploitation ofenergy from waste (incineration, landfill gas, anaerobic digesterbiogas) could be a viable option for many cities in developingcountries. Waste-to-energy programs may be the most prudentoption, where land is scarce or expensive, as it minimizes the use ofland for wastemanagement. The city state of Singapore, where landis extremely scarce, has identified solid waste incineration as themost preferred disposal method (Bai & Sutanto, 2002). In cities,where a larger portion of waste is composed of organic materials,biogasification and composting are some of the other viableoptions. Using a life cycle inventory (LCI), Batool and Chuadhry(2009) show that biogasification is one of the most viable optionfor the Ganj Bukhsh Town (DGBT) in Lahore, Pakistan. In addition toreducing waste volume, biogasification saved 25% in CO2 equiva-lents compared to the baseline scenario. Composting of municipalsolid wastes, where organic wastes constitute a significant portionof solid waste, will not only reduce waste volume but also generaterevenue for cities through compost sales. Composting has GHGreduction benefits. Net GHG emissions from landfills tend to behigher than that from composting facilities (Lou & Nair, 2009).

Conclusion

For cities in developing countries, climate change mitigation isnot the priority. It is a low-priority issue, if anything. Given theresource constraints, they are more interested in allocating theirscarce resources toward pressing local issues. Any or all meaningfulreduction in GHG emissions, hence, will have to come as anoutgrowth of efforts driven by economic, development, servicedelivery, and local environmental concerns, etc. Adoption of thesuggested policy tools outlined in this paper might help cities indeveloping countries meet both local priorities and reduce GHGemissions. In order for these tools to yield maximum climate co-benefits, they will have to be developed within an integratedurban planning and development framework. Often, urban policiesare weak and fragmented. For example, there are separate policesfor various air pollutant reductions even though the activities andsources of many of these pollutants are essentially the same. Thishas resulted in weak enforcement and co-ordination failures of airpollution control policy.

Instead of asking cities in developing countries develop andadopt exclusive urban climate mitigation policies, which theymight do half heartedly, given the funding is made available, donoragencies may want to work closely with cities and help themidentify potential overlaps between energy, air quality, and climategoals and synergies between actions to reach those goals. Theexisting urban GHG mitigation potential can be achieved throughgreater policy integration and coherence. The first step is to definethe objectives of the policy intervention. Depending on theobjectives, for example air pollution or congestion reduction,various combinations of policy tools need to be evaluated againsta range of criteria such as economic efficiency, distributionaleffects, administrative feasibility, and institutional capacity andbundled together.

Whether or not cities in developing countries will be able tocontain or bring about large scale reduction in GHG emissions willlargely depend upon their ability to maximize synergies betweenthe suggested policy tools. It should, however, be noted that policyintegration and coherence can help cities contain rising GHGemissions, but only for a certain period. It is essentially the low-hanging fruit. Eventually cities will have to come up with high-impact solutions. For a long-term sustained reduction of GHGemissions, large scale transformative changes in urban design andinfrastructure, technology, urban lifestyle, energy and wastemanagement, economic and social institutions is necessary.

Acknowledgments

We sincerely thank Chandan Sapkota, Sanjana Dhungana-Dulal,the Editor of the Habitat International Journal, and the anonymousreferees for their valuable comments and suggestions. The viewsexpressed in this paper are solely those of the authors and shouldnot be taken to be the views of the organization to which theauthors are professionally affiliated.

References

ADB (Asian Development Bank). (2002). Study on air quality in Jakarta, Indonesia:Future trends, health impacts, economic value and policy options. Manila,Philippines: ADB.

Amann, M., Bertok, I., Borken, J., Chambers, A., Cofala, J., Dentener, F., et al. (2010).GAINS ASIA e A tool to combat air pollution and climate change simultaneously.Methodology. Laxenburg, Austria: International Institute for Applied SystemsAnalysis.

Bai, R., & Sutanto, M. (2002). The practice and callenges of solid waste managementin Singapore. Waste Management, 22, 557e567.

H.B. Dulal, S. Akbar / Habitat International 38 (2013) 100e105 105Banister, D. (2011). Cities, mobility and climate change. Journal of Transport Geog-raphy, 19(6), 1538e1546.

Batool, S. A., & Chuadhry, M. N. (2009). The impact of municipal solid wastetreatment methods on greenhouse gas emissions in Lahore, Pakistan. WasteManagement, 29(1), 63e69.

Bi, J., Zhang, R., Wang, H., & Liu, M. (2011). The benchmarks of carbon emissions andpolicy implications for Chinas cities: case of Nanjing. Energy Policy, 39(9),4785e4794.

Brueckner, J. K. (2000). Urban sprawl: diagnosis and remedies. InternationalRegional Science Review, 23(2), 160e171.

Cervero, R., & Kockelman, K. (1997). Travel demand and the 3Ds: density, diversity,and design. Transportation Research D, 2, 199e219.

Cohen, B. (2006). Urbanization in developing countries: current trends, futureprojections, and key challenges for sustainability. Technology in Society, 28(1e2),63e80.

Colombo, A., Etkin, D., & Karney, B. (1999). Climate variability and the frequency ofextreme temperature events for nine sites across Canada: implications forpower usage. Journal of Climate, 12(8), 2490e2502.

Creutzig, F., & He, D. (2009). Climate change mitigation and co-benefits of Feasibletransport demand policies in Beijing. Transportation Research D, 14, 120e131.

Deng, X. (2006). Economic costs of motor vehicle emissions in China: a case study.Transportation Research, 11(3), 216e226.

Dodman, D. (2009). Blaming cities for climate change? An analysis of urbangreenhouse gas emissions inventories. Environment and Urbanization, 21(1),185e201.

Dulal, H. B., Brodnig, G., & Onoriose-Green, C. (2011). Climate change mitigation inthe transport sector through urban planning: a review. Habitat International, 35,494e500.

ESCAP (United Nations Economic and Social Commission for Asia and the Pacific).(2007). Sustainable infrastructure in Asia: Overview and proceedings. Seoul,Korea: Seoul Initiative Policy Forum on Sustainable Infrastructure. September6e8, 2006.

European Environment Agency (ESA). (2004). Air pollution and climate changepolicies in Europe: Exploring linkages and the added value of an integratedapproach. Copenhagen: EEA.

Evans, R. (2007). Central London congestion charging scheme: Ex post evaluation of thequantified impacts of the original scheme. London: Transport for London.

Florida, R. (2000). Competing in the age of talent: Quality of place and the neweconomy. report prepared for the R.K. Mellon Foundation, (Heinz Endowmentsand Sustainable Pittsburgh).

Gan, L. (2003). Globalization of the automobile industry in China: dynamics andbarriers in greening of the road transportation. Energy Policy, 31(6), 537e551.

Giuliano, G., & Narayan, D. (2003). Another look at travel patterns and urban form:the US and Great Britain. Urban Studies, 40, 2295e2312.

Hirota, K., Poot, J., & Minato, K. (2003). Do policy incentives affect the environmentalimpact of private car use? Evidence from a sample of large cities. Jyvskyl,Finland: Paper prepared for the 43rd Congress of the European Regional ScienceAssociation. 27-30 August, 2003.

Kirshen, P. H., Ruth, M., Anderson, W., Lakshmanan, T. R., Chapra, S., Chudyk, W.,et al. (2004). Climates long-term impacts on metro Boston. Final Report to the USEPA. Washington, DC: Office of Research and Development. Available online at.

Lin, J., & Yang, A. (2009). Structural analysis of how urban form impacts traveldemand: evidence from Taipei. Urban Studies, 46(9), 1951e1967.

Liu, Z., Geng, Y., & Xue, B. (2011). Inventorying energy-related CO2 for city: Shanghaistudy. Energy Procedia, 5, 2303e2307.

London Climate Change Partnership (LCCP). (2002). A climate change impacts inLondon evaluation study. Final Report November 2002. London: Greater LondonAuthority.

Lou, X. F., & Nair, J. (2009). The impact of landfilling and composting on greenhousegas emissions e a review. Bioresource Technology, 100, 3792e3798.

Lyons, T. J., Kenworthy, J. R., Moy, C., & dos Santos, F. (2003). An international urbanair pollution model for the transportation sector. Transportation Research Part D,8, 159e167.

Messenger, T., & Ewing, R. (1996). Transit-oriented development in the Sun Belt.Transportation Research Record, 1552, 145e153.

Mills, G. (2007). Cities as agents of global change. International Journal ofClimatology, 27, 1849e1857.

OECD. (2010). Cities and climate change. OECD Publishing.Ong, H. C., Mahlia, T. M. I., & Masjuki, H. H. (2011). A review on energy pattern and

policy for transportation sector in Malaysia. Renewable and Sustainable EnergyReviews, 16(1), 532e542.Ou, X., Zhang, X., & Chang, S. (2010). Scenario analysis on alternative fuel/vehicle forChinas future road transport: life-cycle energy demand and GHG emissions.Energy Policy, 38(8), 3943e3956.

Parry, I., & Timilsina, G. (2010). How should passenger travel in Mexico City bepriced? Journal of Urban Economics, 68(2), 167e182.

Patankar, A. M., & Trivedi, P. L. (2011). Monetary burden of health impacts of airpollution in Mumbai, India: implications for public health policy. Public Health,125(3), 157e164.

Pucher, J., Korattyswaropam, N., Mittal, N., & Ittyerah, N. (2005). Urban transportcrisis in India. Transport Policy, 12(3), 185e198.

Ray, A. (2008). Waste management in developing Asia: can trade and cooperationhelp? Journal of Environment & Development, 17(1), 3e25.

Satterthwaite, D., Huq, S., Pelling, M., Reid, H., & Romero Lanako, P. (2007). Adaptingto climate change in urban areas: The possibilities and constraints of low- andmiddle-income nations. London: International Institute for Environment andDevelopment.

Shahraki, S. Z., Sauri, D., Serra, P., Modugno, S., Seifolddini, F., & Pourahmad, A.(2011). Urban sprawl pattern and land-use change detection in Yazd, Iran.Habitat International, 35, 521e528.

Singh, S. (2006). Future mobility in India: implications for energy demand and CO2emission. Transport Policy, 13(5), 398e412.

Smith, W. (1984). Mass transit for high-rise, high-density living. Journal ofTransportation Engineering, 110(6), 521e535.

Sterner, T. (2006). Fuel taxes: an important instrument for climate policy. EnergyPolicy, 35(6), 3194e3202.

Tewolde, M. G., & Cabral, P. (2011). Urban sprawl analysis and modeling in Asmara,Eritrea. Remote Sensing, 3(10), 2148e2165.

Timilsina, G. R., & Dulal, H. B. (2008). Fiscal policy instruments for reducing congestionand atmospheric emissions in the transport sector: A review. World Bank PolicyResearch Working Paper, 4652. Washington, DC: The World Bank.

Timilsina, G. R., & Dulal, H. B. (2009). A Review of regulatory instruments to controlenvironmental externalities from the transport sector. Policy Research WorkingPaper. Washington, D.C: The World Bank.

Timilsina, G. R., & Dulal, H. B. (2010). Urban road transportation externalities: costsand choice of policy instruments. World Bank Research Observer, 26(1), 162e191.

Town of Brattleboro. (2003). The climate action plan -A plan to save energyand reduce greenhouse gas emissions. Cities for climate protection campaign.International Council of Local Environmental Initiatives. Available online at.

Transport for London. (2004). High level voluntary environmental Assessment oftransport strategy revision: Central London congestion charging: Environmentalassessment. Annex of Report to the Mayor. http://www.tfl.gov.uk/tfl/cc-ex/reports.shtml.

UNHABITAT. (2010). Urban trends: Urban sprawl now a global problem. Nairobi,Kenya: UNHABITAT.

United Nations Environment Programme. (2011). Towards a green economy: Path-ways to sustainable development and poverty eradication. Nairobi: UNEP.

United Nations Environment Programme (UNEP). (2010). Green economy: developingcountries success stories. Nairobi: UNEP.

United Nations (UN). (2006). World urbanization prospects: The 2005 revision. NewYork: UNDESA.

United Nations (UN). (2007). World urbanization prospects: The 2007 revisionpopulation database. New York: United Nations.

United States Environmental Protection Agency (US EPA). (2006). Globalanthropogenic non-CO2 greenhouse gas emissions: 1990-2020. Available onlineat. Office of Atmospheric Programs, Climate Change Division .

Vigui, V., & Hallegatte, S. (2012). Trade-offs and synergies in urban climate policies.Nature Climate Change, . doi:10.1038/NCLIMATE1434.

Willoughby, C. (2000). Singapores experience in managing motorization, and itsrelevance to other countries. Discussion PaperTWU-43. Washington DC: TheWorld Bank.

World Bank. (2002). Environment monitor 2002. Air Quality (Philippines andThailand Country Reports). Washington, DC: The World Bank.

Zhang, D. Q., Tan, S. K., & Gersberg, R. M. (2010). Municipal solid waste managementin China: status, problems and challenges. Journal of EnvironmentalManagement, 91(8), 1623e1633.

Zhou, N., & McNeil, M. A. (2009). Assessment of historic trend in mobility andenergy use in India transportation sector using bottom-up approach. Journal ofRenewable and Sustainable Energy, 4, 3108e3124.

http://www.tufts.edu/tie/pdf/CLIMBFV1-8_10pdf.pdfhttp://www.brattleboro.org/vertical/Sites/%257BF60A5D5E-AC5C-4F97-891A-615C172A5783%257D/uploads/%257B8E554F52-EB49-422F-8E2A-C90242FDF15B%257D.PDFhttp://www.brattleboro.org/vertical/Sites/%257BF60A5D5E-AC5C-4F97-891A-615C172A5783%257D/uploads/%257B8E554F52-EB49-422F-8E2A-C90242FDF15B%257D.PDFhttp://www.brattleboro.org/vertical/Sites/%257BF60A5D5E-AC5C-4F97-891A-615C172A5783%257D/uploads/%257B8E554F52-EB49-422F-8E2A-C90242FDF15B%257D.PDFhttp://www.tfl.gov.uk/tfl/cc-ex/reports.shtmlhttp://www.tfl.gov.uk/tfl/cc-ex/reports.shtmlhttp://www.epa.gov/ngs/econ-inv/downloads/GlobalAnthroEmissionsReport.pdfhttp://www.epa.gov/ngs/econ-inv/downloads/GlobalAnthroEmissionsReport.pdf

Greenhouse gas emission reduction options for cities: Finding the Coincidence of Agendas between local priorities and cli ...IntroductionCan cities continue to afford undermining growing emissions?Leveraging local priorities for urban green house gas reductionUrban development interventionsUrban transport interventionsInfrastructure interventionsWaste sector interventions

ConclusionAcknowledgmentsReferences